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st: testing fixed effects versus random effects for clustered data using overiden
From
Ridhima Gupta <[email protected]>
To
[email protected]
Subject
st: testing fixed effects versus random effects for clustered data using overiden
Date
Mon, 28 Feb 2011 14:46:15 +0000
Hello,
I don't have a panel data in the strict sense of the term i.e. I have
data on farmers who have several plots/fields. I first perform a
standard hausman test and I do not reject the
null hypothesis of random effects. The result is as follows:
hausman fixed ., sigmamore
---- Coefficients ----
| (b) (B) (b-B) sqrt(diag(V_b-V_B))
| fixed . Difference S.E.
-------------+----------------------------------------------------------------
Happy_Seeder | .1271123 .5428827 -.4157704 .429518
Rotavator | -.3621306 -.3157851 -.0463455 .840699
Seed_Drill | -.083707 .860967 -.944674 .5539517
quantity_s~c | .0056369 -.0031733 .0088101 .0188915
plotsize_hec | .0252054 .0310519 -.0058465 .0525993
ferti_hec | .0027516 .003003 -.0002514 .0045816
exp_weedi_~s | .1077859 .0282141 .0795719 .0585852
soil_type_1 | -1.034988 -1.900228 .8652395 .6801256
soil_type_2 | -.4202215 -2.165068 1.744846 .8051986
------------------------------------------------------------------------------
b = consistent under Ho and Ha; obtained from xtreg
B = inconsistent under Ha, efficient under Ho; obtained from xtreg
Test: Ho: difference in coefficients not systematic
chi2(9) = (b-B)'[(V_b-V_B)^(-1)](b-B)
= 12.70
Prob>chi2 = 0.1766
But when I perform the robust version of this test, I reject the null
hypothesis of random effects.
Random-effects GLS regression Number of obs = 227
Group variable: hh_id Number of groups = 86
R-sq: within = 0.0106 Obs per group: min = 1
between = 0.0922 avg = 2.6
overall = 0.0674 max = 6
Random effects u_i ~ Gaussian Wald chi2(9) = 15.76
corr(u_i, X) = 0 (assumed) Prob > chi2 = 0.0720
(Std. Err. adjusted for 86 clusters in hh_id)
------------------------------------------------------------------------------
| Robust
yield_per_~c | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
Happy_Seeder | .5428827 1.024596 0.53 0.596 -1.465289 2.551054
Rotavator | -.3157851 1.425605 -0.22 0.825 -3.10992 2.47835
Seed_Drill | .860967 1.036252 0.83 0.406 -1.170049 2.891983
quantity_s~c | -.0031733 .041733 -0.08 0.939 -.0849685 .078622
plotsize_hec | .0310519 .0467653 0.66 0.507 -.0606065 .1227103
ferti_hec | .003003 .0053299 0.56 0.573 -.0074435 .0134495
exp_weedi_~s | .0282141 .0792311 0.36 0.722 -.1270759 .1835041
soil_type_1 | -1.900228 .7639786 -2.49 0.013 -3.397599 -.4028574
soil_type_2 | -2.165068 .8668351 -2.50 0.013 -3.864033 -.4661022
_cons | 41.85728 4.370738 9.58 0.000 33.29079 50.42376
-------------+----------------------------------------------------------------
sigma_u | 4.4041886
sigma_e | 4.0351113
rho | .54364968 (fraction of variance due to u_i)
------------------------------------------------------------------------------
. xtoverid
Test of overidentifying restrictions: fixed vs random effects
Cross-section time-series model: xtreg re robust cluster(hh_id)
Sargan-Hansen statistic 26.327 Chi-sq(9) P-value = 0.0018
Is there any inconsistency here? Are there any tests in the literature
that allow me to test the assumption of homoskedasticity and no
auto-correlation in the random effects model?
Thanks a lot,
Ridhima
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